DTO-SMOTE: Delaunay Tessellation Oversampling
for Imbalanced Data Sets

DTO-SMOTE: Delaunay Tessellation Oversampling for Imbalanced Data Sets

One of the significant challenges in machine learning is the classification of imbalanced<br />data. In many situations, standard classifiers cannot learn how to distinguish minority class<br />examples from the others. Since many real problems are unbalanced, this problem has become<...

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Bibliographic Details
Main Authors:	Alexandre M. de Carvalho, Ronaldo C. Prati
Format:	Article
Language:	English
Published:	MDPI AG 2020-11-01
Series:	Information
Subjects:	machine learning SMOTE oversampling DTO-SMOTE imbalanced data
Online Access:	https://www.mdpi.com/2078-2489/11/12/557

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